Shruti Joshi is a visiting researcher at ServiceNow. Her research interests are in the fields of reinforcement learning, representation learning, and causal inference. How can we sample-efficiently learn decision-making policies on diverse, open-world data? What kind of world models provide meaningful representations about objects and other entities to an agent interacting with its environment? What causal information can we already incorporate towards solving the credit assignment problem, and how do we uncover the underlying causal structure of the decision-making problem? These are some of the questions that motivate her current research. She is also interested in better software design to reliably test out her research hypotheses. She continues to learn how to build well-maintained (!) iterative codebases and how to debug better and visualize her work, not letting pesky bugs steal her motivation.